Historically, the diagnosis of diseases has depended upon clinical manifestations. However, new techniques of detecting diseases have been developed with the advent of monoclonal antibody and nucleic acid detection methods. The detection of nucleic acid has been used for diseases associated with abnormal gene products, such as anemia, Huntington's disease and certain thalassemia mutations. In addition, the detection of nucleic acid has been used for bacterial and viral diseases, such as Human Immunodeficiency Virus (HIV). Moreover, nucleic acid detection methods have been applied to detect water and food contaminations, such as E.coli contamination.
As appreciated by those skilled in the art, the detection of a pathogen indicator has applicability to the detection of certain diseases associated with abnormal genes, certain diseases associated with the presence of an identifiable nucleic acid sequence and certain diseases associated with the immune system. The pathogen indicator described herein includes DNA, RNA, antibody, antigen, and other proteins.
Known manual pathogen indicator detection methods in research and clinical laboratories tend to have low accuracy, low sensitivity and are subject to human error, both in carrying out the methods and in interpreting the results. Other methods, e.g. culturing methods, are not suitable for many diseases. For example, tuberculosis has a very slow growth rate, which makes detection difficult or even not possible. Most of the previous tests are demanding of time, skill and concentration. So much so, that in many jurisdictions the number of tests that can be conducted by one technician is limited by regulation. This serves to raise the cost of testing, as it is so labor dependent.
On the other hand, in many clinical tests, multiple test materials, such as multiple nucleic acid fragments, in a test sample need to be detected for proper diagnosis of a disease, or for identifying proper cause of a clinical condition. Sometimes, a multiple target analysis not only confirms the presence of certain microorganism, but also identifies the species of the organism, which is important for determination of proper treatments. For example, in the case of determining E. Coli contamination of water or food, at least three genes need to be detected in a sample, wherein positive results in at least two genes confirm the presence of the bacteria. Currently, the multiple test material detections are performed separately. It is known that a small amount of bacteria E. Coli can cause diseases. Therefore, dividing available sample, particularly when it is limited, for three separate tests reduces accuracy of the detections and the detection limits.
U.S. Pat. No. 5,804,384 to Muller et al. discloses devices that each include a vessel or a channel containing a linear array of binding elements, each having a binding factor, or probe, specific for a distinct target analyte. The devices can be used in methods for the simultaneous analysis of multiple analytes in a sample. Muller et al. teach that because detected analytes are physically separated on the devices, it is not necessary to use distinct labels on the detector probes that are specific for different analytes.
U.S. Pat. No. 5,876,918 to Wainwright et al. discloses a preactivated chromatography tip having multi-layered receptor elements. In a typical format of three layers of receptor, one layer is for the target analyte, and two layers are for positive and negative controls which contain pre-bound positive and negative controls, respectively. The receptor elements, including controls, are designed specifically for a single analyte for which the detection is sought. This method and device are not suitable for multiple target material analysis. Furthermore, the pre-bound controls do not reflect analyte binding and other reaction conditions that the target material experiences.
For all the above reasons, a new method and apparatus for detecting multiple test materials, particularly multiple nucleic acid fragments, in a sample with a true in-line control is desirable, which is accurate, less costly, and is sensitive to determining if there is an error in the method.